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Discussion papers
https://doi.org/10.5194/os-2016-105
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-2016-105
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 16 Jan 2017

Research article | 16 Jan 2017

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This discussion paper is a preprint. A revision of the manuscript for further review has not been submitted.

An Ensemble Observing System Simulation Experiment of Global Ocean Heat Content Variability

Arin D. Nelson1, Jeffrey B. Weiss1, Baylor Fox-Kemper2, Royce K. P. Zia3, and Fabienne Gaillard4 Arin D. Nelson et al.
  • 1Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado, USA
  • 2Department of Earth, Environmental, and Planetary (DEEP) Sciences, Brown University, Providence, Rhode Island, USA
  • 3Center for Soft Matter and Biological Physics, Department of Physics, Virginia Polytechnical Institute and State University, Blacksburg, Virginia, USA
  • 4Ifremer, UMR 6523, LOPS, CNRS/Ifremer/IRD/UBO, CS 10070, Plouzane F-29280, France

Abstract. We quantify skill and uncertainty in observing the statistics of natural variability using observing system simulation experiments on an ensemble of climate simulations and an observing strategy of in situ measurements and objective mapping. The targeted statistic is the 0–700 m global ocean heat content anomaly as observed by the In Situ Analysis System 2013 (ISAS13) strategy of a long, equilibriated simulation of the Community Climate System Model (CCSM) version 3.5. Subannual variability is found to be significantly contaminated by the observing strategy, especially before 2005, primarily due to the sparseness and seasonality in the number and location of pre-Argo observations. However, one-year running means from 2005 onward are found to faithfully capture the natural variability of the model's true ocean heat content variability. During these years, synthetic observed annual running means are strongly correlated with the actual annual running means of the model, with a median correlation of 95 %, versus only 60 % for the observational record before 2005. When scaled to account for the fact that the real ocean is more variable than the model, root mean square errors in observing the annual-running mean natural variability of the global ocean heat content are estimated to be 6.2 ZJ for the pre-Argo era (1990–2005) and 2.1 ZJ for the Argo era (2005–2013) with relative signal-to-noise ratios of 1.9 and 14.7. Combining the estimated, scaled uncertainties of the observing strategy with its estimated trend, the 1990–2013 trend in global ocean heat content is found to be 5.3 ± 1.0 ZJ/yr.

Arin D. Nelson et al.
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Interactive discussion
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Arin D. Nelson et al.
Arin D. Nelson et al.
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Short summary
We quantify the skill in observing the variability of global upper ocean heat content (OHC) by applying the ISAS13 observing strategy to a CCSM simulation. We find that variability is unreliably observed before 2005, while observed annual running means for 2005–2013 correlate well with model "truth" to a median of 95 %. When scaled to the real ocean, we find signal-to-noise ratios of 1.9 for pre-Argo times (1990–2005) and 14.7 after Argo is introduced (2005–2013). The global warming is robust.
We quantify the skill in observing the variability of global upper ocean heat content (OHC) by...
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